From Ars Technica: Nobel Intent, a thought-provoking article on what the prevalence of computational science portends for reproducibility in science:

Victoria Stodden is currently at Yale Law School, and she gave a short talk at the recent Science Online meeting in which she discussed the legal aspects of ensuring that the code behind computational tools is accessible enough for reproducibility. The obvious answer is some sort of Creative Commons or open source license, and Stodden is exploring the legal possibilities in that regard. But she makes a forceful argument that some form of code sharing will be essential.

“You need the code to see what was done,” she told Ars. “The myriad computational steps taken to achieve the results are essentially unguessable—parameter settings, function invocation sequences—so the standard for revealing it needs to be raised to that of when the science was, say, lab-based experiment.” This sort of openness is also in keeping with the scientific standards for sharing of more traditional materials and results. “It adheres to the scientific norm of transparency but also to the core practice of building on each other’s work in scientific research,” she said. But the same worries that apply to more traditional data sharing—researchers may have a competitor use that data to publish first—also apply here. In the slides from her talk, she notes that a survey she conducted of computational scientists indicates that many are concerned about attribution and the potential loss of publications in addition to legal issues. (The biggest worry is the effort involved to clean up and document existing code.)

Still, this sort of disclosure, as with other open source software, should provide a key benefit: more interested parties able to evaluate and improve the code. “Not only will we clearly publish better science, but redesigned and updated code bases will be valuable scientific contributions,” Stodden said. “Over time, we won’t stagnate forever on one set of published code.”